stationary process
Quick Summary
A stationary process is a type of stochastic process where the statistical properties, such as mean, variance, and autocorrelation, remain constant over time. This means the behavior of the process is the same regardless of when it is observed. A simple example is a sequence of independent, identically distributed random variables. Stationary processes are crucial in time series analysis, as models like ARIMA require the data to be stationary to make accurate forecasts. If a process is not stationary, techniques like differencing can sometimes transform it into a stationary one.12
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